ROBiri - Grup de Percepció i Manipulació Robotitzada de l'IRI
La recerca s'articula en dues línies amb els objectius que es detallen a continuació.
Percepció i Manipulació:
1. Enllaçar percepció i acció utilitzant mètodes geomètrics i estadístics per al modelatge de l'entorn i del propi robot, per a la planificació de tasques i moviments, i per a l'aprenentatge.
2. Aprofundir en l'aprenentatge per reforçament i en l'aprenentatge per demostració, en particular el "mestratge", com a base per a la interacció entre robots, humans i l'entorn.
Cinemàtica i Disseny de Robots:
3. Trobar mètodes generals i complets per a l'anàlisi i la planificació de moviments lliures de col·lisió de mecanismes.
4. Desenvolupar noves estructures mecàniques, preferentment robots paral·lels i robots basats en estructures "tensegrity".
5. Incrementar i millorar l'expertesa del grup en l'àrea del disseny mecànic
La investigación se articula en dos líneas con los objectivos que se detallan a continuación.
Percepción y Manipulación:
1. Enlazar percepción y acción utilitzando métodos geométricos y estadísticos para el modelado del entorno y del propio robot, para la planificación de tareas y movimientos, y para el aprendizaje.
2. Profundizar en el aprendizaje por refuerzo y en el aprendizaje por demostración, en particular el entrenamiento, como base para la interacción entre robots, humanos y el entorno.
Cinemática y Diseño de Robots:
3. Encontrar métodos generales y completos para análisis y planificación de movimientos libres de colisión.
4. Desarrollar nuevas estructuras mecánicas, preferentmente robots paralelos y robots "tensegrity".
5. Incrementar y mejorar la competencia del grupo en el área del diseño mecánico.
Research is organized in two lines with the following goals.
Perception and Manipulation:
1. Linking perception and action using geometric and statistic methods for modelling the environment and the robot, for task and motion planning, and for learning.
2. Deepening on reinforcement learning and in learning by demonstration, in particular "coaching", as a basis for the interaction of robots, humans and the environtment.
Kinematics and Robot Design:
3. Finding general and complete methods for the analysis of mechanisms and for planning collision-free motions.
4. Developing new mechanical structures, especially parallel robots and robots based on tensegrity structures.
5. Increasing and enhancing the expertise of the group in the area of mechanical design.
Research is organized in two lines with the following goals.
Perception and Manipulation:
1. Linking perception and action using geometric and statistic methods for modelling the environment and the robot, for task and motion planning, and for learning.
2. Deepening on reinforcement learning and in learning by demonstration, in particular "coaching", as a basis for the interaction of robots, humans and the environtment.
Kinematics and Robot Design:
3. Finding general and complete methods for the analysis of mechanisms and for planning collision-free motions.
4. Developing new mechanical structures, especially parallel robots and robots based on tensegrity structures.
5. Increasing and enhancing the expertise of the group in the area of mechanical design.
Collections in this community
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Articles de revista [168]
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Capítols de llibre [23]
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Llibres [3]
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Reports de recerca [24]
Recent Submissions
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Uncalibrated, unified and unsupervised specular-aware photometric stereo
(Springer, 2023)
Conference report
Open AccessIn this paper we present a variational approach to simultaneously recover the 3D reconstruction, reflectance, lighting and specularities of an object, all of them, from a set of RGB images. The approach works in an ... -
Context attention: human motion prediction using context information and deep learning attention models
(Springer, 2022)
Conference lecture
Open AccessThis work proposes a human motion prediction model for handover operations. The model uses a multi-headed attention architecture to process the human skeleton data together with contextual data from the operation. This ... -
Towards transferring tactile-based continuous force control policies from simulation to robot
(2023)
Conference report
Open AccessThe advent of tactile sensors in robotics has sparked many ideas on how robots can leverage direct contact measurements of their environment interactions to improve manipulation tasks. An important line of research in this ... -
Back to MLP: a simple baseline for human motion prediction
(Institute of Electrical and Electronics Engineers (IEEE), 2023)
Conference report
Open AccessThis paper tackles the problem of human motion prediction, consisting in forecasting future body poses from historically observed sequences. State-of-the-art approaches provide good results, however, they rely on deep ... -
Visual semantic relatedness dataset for image captioning
(2023)
Conference report
Open AccessModern image captioning system relies heavily on extracting knowledge from images to capture the concept of a static story. In this paper, we propose a textual visual context dataset for captioning, in which the publicly ... -
NeRFLight: Fast and Light Neural Radiance Fields using a shared feature grid
(Institute of Electrical and Electronics Engineers (IEEE), 2023)
Conference report
Open AccessWhile original Neural Radiance Fields (NeRF) have shown impressive results in modeling the appearance of a scene with compact MLP architectures, they are not able to achieve real-time rendering. This has been recently ... -
Els reptes de la robòtica assistencial: memòria llegida per l'acadèmica electa Dra. Carme Torras i Genís, a l'acte de la seva recepció el dia 16 de febrer de 2017
(2017)
Article
Open AccessEls robots ja no estan confinats a les fàbriques, sinó que els anirem trobant cada vegada més en entorns urbans, socials i assistencials. Per arribar a ser companys de feina eficaços i assistents útils, han d’estar dotats ... -
User interactions and negative examples to improve the learning of semantic rules in a cognitive exercise scenario
(2023)
Conference report
Open AccessEnabling a robot to perform new tasks is a complex endeavor, usually beyond the reach of non-technical users. For this reason, research efforts that aim at empowering end-users to teach robots new abilities using intuitive ... -
Photovoltaic power forecasting using sky images and sun motion
(Institute of Electrical and Electronics Engineers (IEEE), 2023)
Conference report
Open AccessSolar energy adoption is moving at a rapid pace. The variability in solar energy production causes grid stability issues and hinders mass adoption. To solve these issues, more accurate photovoltaic power forecasting systems ... -
Gaussian-process-based robot learning from demonstration
(Springer, 2023-02-22)
Article
Open AccessLearning from demonstration allows to encode task constraints from observing the motion executed by a human teacher. We present a Gaussian-process-based learning from demonstration (LfD) approach that allows robots to learn ... -
A novel collision model for inextensible textiles and its experimental validation
(Elsevier, 2024-04)
Article
Open AccessIn this work, we introduce a collision model specifically tailored for the simulation of inextensible textiles. The model considers friction, contacts, and inextensibility constraints all at the same time without any ... -
NYAM: the role of configurable engagement strategies in robotic-assisted feeding
(2024)
Conference report
Restricted access - publisher's policyIn some contexts, like geriatric hospitals, the number of patients requiring assistance with feeding is very high and robots may be an effective tool for caregivers to provide better assistance. This article introduces ...
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